Assuming that digital media is just another tool for human communication I would agree that these automated analyses alone can not really do a good job in interpreting human feelings by analysing vocabulary in a text that can be seen as a human expression that stands at the end of a more or less long chain of reactions (in our nervous system) that might happen between reception and final resulting behaviour. We know that misunderstandings in communication are a common case because of the many different ways people use language. Too many influence factors form the way we use it and the way how we understand it (cultural, religious, social background, education, criterias and believes, knowledge and abilities, decisions, memories, … = can be summarized as our personality?). There are even some people who have their difficulties to understand their own feelings or to distinguish between their own words (or verbalized feelings/sentiment) and their experience (inner or outer).

Wouldn’t it be similar trying to find a theory that suggests the sentiment or intention of the artist while creating an oil painting based on the color combinations used and color density or based on a geometrical area analysis? In some cases it could also be possible that the artist changed his intention during the creation process. How does it influence the resulting expression?

No. Currently I do not see a way how a software can fill in all the gaps that exist by not knowing all the deletions, generalizations and distortions that come into play when we begin to use language.

Without a doubt, these tools can do a great job analyzing according to predefined criterias and they will also help you managing this big amount of information in a much shorter time (than without these tools). And only in combination with your (human) synthesis, this kind of software supported analysis can bring out more useful results that could lead to better decisions.

Best regards.

I couldn’t agree more and sentiment is but one piece of a meaningful measurement program. Sentiment’s greatest value comes when viewing it in relation to other qualitative metrics, such as topics or brand attributes, which are coded by humans versus the existence of keywords. A dependence on the use of keywords can cloud an analysis because it sets artificial limits for metric values as they are generated based on preconceived notions as opposed to the content at hand. There is no substitute for human analysis, and not just from an accuracy standpoint, but also in ensuring that content is qualified in the first place and void of “noise” such as ads, spam sites and listings. In the end, it’s nice to be able to confidently communicate *why* coverage was negative instead of just stating a percentage.

Also, I love your point about the satisfaction gained from being “invested” in the data… so true. Thanks for sharing, Mike.

I’m doing quite a lot of buzzmonitoring for brands and of course use automated tool. It only helps to measure the amount of mentions. To be honest the sentiment is not often accurate. Because when people use irony or humor, the data is the opposite sentiment. The human checking is an absolute necessity.

[...] assumptions and very little code we're able to get almost 73% accuracy. This is somewhat near human accuracy, as apparently people agree on sentiment only around 80% of the time. Future articles in this [...]

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Having human oversight is vital for sentiment analysis. But automated sentiment analysis can work much better if you understand how to use it correctly. Here’s my blog post on how to effectively use today’s technology to make the best of sentiment analysis:
http://www.mutualmind.com/blog/2010/07/10-ways-effectively-use-sentiment-analysis-social-media/

Babar
Founder, MutualMind.